Methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating suggested search queries. One method includes receiving, during a search session, a request for a suggested search query; in response to receiving the request for the suggested search query, identifying an entity that is associated with an item of media content; generating a suggested search query based on the identified entity; and providing data that causes the generated suggested search query to be presented in a user interface.
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2. The method of claim 1, wherein the spoken request comprises a spoken, incomplete search request or other partial voice command.
A system and method for processing incomplete or partial voice commands in a voice-based search or command interface. The technology addresses the challenge of users providing ambiguous or incomplete spoken requests, which can lead to inaccurate or failed search results or command execution. The method involves receiving a spoken request that is incomplete or partially formed, such as a fragmented search query or a voice command that lacks necessary details. The system analyzes the incomplete request to identify its intent and context, then generates a refined or completed version of the request based on user preferences, historical data, or contextual clues. This may involve predicting missing elements, disambiguating ambiguous terms, or suggesting possible completions to the user for confirmation. The refined request is then processed to execute the intended search or command. The method may also include adaptive learning to improve future request interpretations based on user feedback or corrections. This approach enhances the usability and accuracy of voice interfaces by handling incomplete or partial inputs effectively.
3. The method of claim 1, wherein the prompt comprises an autocompleted portion of a spoken, incomplete search request.
This invention relates to search systems that enhance user experience by providing autocompleted suggestions for incomplete spoken search requests. The problem addressed is the inefficiency and frustration users face when manually completing partial or unclear voice queries, leading to slower search results or incorrect interpretations. The solution involves generating a prompt that includes an autocompleted portion of the spoken, incomplete search request. This prompt is derived from analyzing the user's partial input and predicting the most likely intended query based on contextual, linguistic, or historical data. The system dynamically fills in missing or ambiguous parts of the spoken request to improve accuracy and reduce user effort. The autocompletion process may involve natural language processing (NLP) techniques, machine learning models trained on prior search patterns, or real-time contextual analysis. The completed prompt is then used to execute the search, ensuring faster and more relevant results. This approach is particularly useful in voice-activated systems, virtual assistants, or any interface where spoken input may be fragmented or unclear. The invention aims to bridge the gap between incomplete user input and the intended search query, enhancing usability and efficiency in search interactions.
4. The method of claim 1, wherein the item of media content comprises a song played by a different device during the time window.
This invention relates to media content synchronization systems, specifically addressing the challenge of coordinating media playback across multiple devices to enhance user experience. The system detects and synchronizes media content, such as songs, played by different devices within a defined time window. When a song is identified as being played by a second device during the same time window as a primary device, the system adjusts playback on the primary device to align with the secondary device's playback. This ensures seamless transitions, avoids disruptions, and maintains continuity in media playback across devices. The synchronization process may involve adjusting playback speed, pausing, or resuming playback to match the secondary device's timeline. The invention improves user experience by preventing playback conflicts and ensuring consistent media delivery across multiple devices in a networked environment. The system is particularly useful in smart home environments, multi-device entertainment setups, and collaborative media playback scenarios.
5. The method of claim 1, wherein the background audio data is a snippet of audio, captured during the time window by the microphone of the digital assistant device, from a song played by a different device.
This invention relates to digital assistant devices that capture and analyze background audio data to enhance user interactions. The problem addressed is the difficulty in identifying and utilizing ambient audio, such as music playing from nearby devices, to improve the functionality of digital assistants. The method involves capturing a snippet of audio during a specific time window using the microphone of the digital assistant device. This audio snippet is from a song or other audio content played by a different device in the vicinity. The captured audio is then processed to identify its source, such as the title, artist, or other metadata associated with the song. This information can be used to provide context-aware responses, suggest related actions, or enhance the user experience by integrating the ambient audio into the digital assistant's operations. The method ensures that the digital assistant can recognize and leverage background audio without requiring explicit user input, making interactions more seamless and intuitive. The system may also filter or prioritize the captured audio to distinguish relevant content from noise, improving accuracy in identifying the source of the audio. This approach enhances the digital assistant's ability to operate in dynamic environments where multiple audio sources may be present.
6. The method of claim 1, wherein spoken request is provided to an automated speech recognizer, and the entity search system is an automated music recognizer.
This invention relates to automated systems for processing spoken requests to identify and retrieve specific entities, particularly in the context of music recognition. The problem addressed is the need for efficient and accurate systems that can interpret spoken queries and match them to relevant entities, such as songs, artists, or albums, using automated speech and music recognition technologies. The method involves receiving a spoken request from a user, which is then processed by an automated speech recognizer to convert the spoken input into a textual or digital representation. This processed request is subsequently analyzed by an automated music recognizer system, which compares the input against a database of known music-related entities. The system identifies the most relevant entity based on the spoken request, enabling users to quickly and accurately retrieve desired music-related information. The automated speech recognizer ensures that the spoken input is accurately transcribed, while the automated music recognizer leverages advanced algorithms to match the transcribed request to the correct entity. This combination of technologies enhances the precision and reliability of the system, making it suitable for applications such as voice-activated music search, recommendation systems, and digital music libraries. The invention improves user experience by reducing the need for manual input and minimizing errors in entity recognition.
7. The method of claim 1, wherein the prompt incorporates a name of the item of media content.
This invention relates to systems for generating or modifying media content, such as images, videos, or audio, based on user input. The problem addressed is the lack of precision in content generation when relying solely on generic prompts, leading to irrelevant or mismatched outputs. The solution involves refining the generation process by incorporating specific identifiers, such as the name of the item of media content, into the input prompt. This ensures the generated or modified content aligns more closely with the user's intent. The method may include preprocessing the input to extract or verify the name of the item, then integrating it into a structured prompt that guides the generation or modification process. The system may also validate the name against a database or metadata to ensure accuracy. This approach improves the relevance and coherence of the output, particularly in applications like personalized content creation, automated editing, or adaptive media generation. The invention may be applied in various domains, including digital art, video editing, and audio synthesis, where precise control over content is critical.
9. The system of claim 8, wherein the spoken request comprises a spoken, incomplete search request or other partial voice command.
A system processes spoken requests, including incomplete search queries or partial voice commands, to facilitate user interactions with a computing device. The system includes a voice input module that captures and interprets spoken input from a user. A natural language processing (NLP) module analyzes the spoken request to identify its intent and extract relevant keywords or phrases, even if the request is incomplete or partially formed. A search or command execution module then processes the interpreted request, either by completing the incomplete search query based on context, user history, or other data, or by executing a partial command to the extent possible. The system may also include a feedback mechanism to prompt the user for additional input if the request is ambiguous or insufficient for full execution. The system is designed to enhance user convenience by allowing flexible, natural language interactions, particularly in scenarios where users may not provide fully formed commands or queries. The technology addresses the challenge of interpreting and acting on incomplete or partially articulated voice inputs, improving accessibility and usability in voice-controlled environments.
10. The system of claim 8, wherein the prompt comprises an autocompleted portion of a spoken, incomplete search request.
The invention relates to a system for enhancing search functionality by providing autocompleted portions of spoken, incomplete search requests. The system is designed to improve user experience in voice-based search interfaces by predicting and completing partial or ambiguous spoken queries in real-time. This addresses the challenge of accurately interpreting and responding to incomplete or unclear voice inputs, which can lead to frustration and inefficiency in traditional search systems. The system includes a voice input module that captures spoken search requests from a user. An analysis module processes the incomplete or ambiguous spoken input to identify potential completions. A completion module generates one or more autocompleted versions of the spoken request based on contextual, linguistic, or historical data. The system then presents these autocompleted options to the user, allowing them to select the most relevant completion or refine their query further. This predictive capability reduces the need for repeated or corrected inputs, improving the speed and accuracy of voice-based searches. The system may also integrate with existing search engines or databases to retrieve results based on the autocompleted query, ensuring seamless integration with current search technologies. By leveraging natural language processing and machine learning, the system adapts to user preferences and patterns, enhancing its predictive accuracy over time. This invention is particularly useful in applications such as virtual assistants, smart devices, and voice-activated search interfaces.
11. The system of claim 8, wherein the item of media content comprises a song played by a different device during the time window.
A system for synchronizing media playback across multiple devices detects and analyzes media content being played by a different device within a defined time window. The system identifies the song being played by the other device and synchronizes playback of the same song on a primary device, ensuring both devices play the same content simultaneously. The synchronization process may involve adjusting playback timing, volume, or other audio parameters to align the media content between the devices. This system is particularly useful in environments where multiple devices are present, such as home entertainment setups or collaborative workspaces, to prevent playback conflicts and enhance user experience. The system may also include features to detect and resolve discrepancies in playback, such as adjusting for latency or buffering delays, to maintain synchronization. Additionally, the system may support user preferences or settings to customize synchronization behavior, such as prioritizing one device over another or allowing manual adjustments. The technology addresses the problem of unsynchronized media playback across devices, which can lead to disruptions or a degraded listening experience.
12. The system of claim 8, wherein the background audio data is a snippet of audio, captured during the time window by the microphone of the digital assistant device, from a song played by a different device.
A digital assistant system captures background audio data, specifically a short audio snippet, during a time window using the microphone of the digital assistant device. This audio snippet originates from a song played by a separate device, not the digital assistant itself. The system processes this background audio to identify or analyze the song, enabling features such as song recognition, contextual awareness, or user interaction based on the detected audio. The system may use the identified song to provide relevant information, adjust device settings, or enhance user experience by integrating the audio context into its operations. The digital assistant device operates independently of the device playing the song, ensuring that the captured audio is from an external source. This functionality allows the digital assistant to recognize and respond to ambient audio, improving its ability to interact with users in environments where music or other audio is present. The system may further include components for audio processing, storage, and analysis to accurately identify and utilize the background audio data.
13. The system of claim 8, wherein spoken request is provided to an automated speech recognizer, and the entity search system is an automated music recognizer.
The invention relates to automated speech and music recognition systems designed to process spoken requests and identify music. The system addresses the challenge of accurately interpreting user queries and matching them with relevant music content in an automated manner. The core functionality involves receiving a spoken request from a user, which is then processed by an automated speech recognizer to convert the spoken input into a machine-readable format. This processed request is subsequently analyzed by an automated music recognizer, which identifies and retrieves the corresponding music based on the recognized speech input. The system integrates speech recognition and music recognition technologies to streamline the process of accessing music through voice commands, enhancing user convenience and efficiency. The automated music recognizer may employ algorithms to compare the recognized speech input with a database of music titles, artists, or other metadata to accurately match the user's request with the desired music. This approach eliminates the need for manual input, reducing errors and improving response times in music retrieval systems. The system is particularly useful in applications such as voice-activated music players, smart assistants, and automated recommendation engines.
14. The system of claim 8, wherein the prompt incorporates a name of the item of media content.
A system for generating personalized media content recommendations incorporates a user's preferences and contextual data to enhance the relevance of suggestions. The system analyzes user behavior, such as past interactions with media content, to identify patterns and preferences. It also considers contextual factors like time of day, location, or device type to tailor recommendations. The system includes a prompt generation module that creates queries or prompts to retrieve relevant media content from a database. These prompts are dynamically adjusted based on the user's historical data and real-time context. The system further includes a recommendation engine that processes the generated prompts to select and rank media content items for presentation to the user. The system may also incorporate feedback mechanisms to refine future recommendations based on user responses. In this specific embodiment, the prompt generation module includes the name of the item of media content to improve the accuracy and specificity of the recommendations. This ensures that the system can directly reference known or preferred content, enhancing personalization and user satisfaction. The system is designed to operate across various media types, including audio, video, and text, and can be integrated into streaming platforms, social media, or other digital content delivery services.
17. The non-transitory computer-readable storage medium of claim 15, wherein the item of media content comprises a song played by a different device during the time window.
A system and method for analyzing media content interactions involves detecting when a user interacts with a media item, such as a song, during a specific time window. The system identifies the media item by analyzing audio data captured by a user device, such as a smartphone, during the interaction. The audio data is processed to determine whether the media item is being played by a different device, such as a nearby speaker or another user's device. The system then associates the interaction with the identified media item, even if the media item is not directly played by the user's device. This allows for tracking and analyzing media consumption patterns across multiple devices and environments. The system may also compare the captured audio data with reference audio data to confirm the identity of the media item. The method improves media analytics by accurately attributing interactions to specific media items, regardless of the playback source. This is particularly useful in scenarios where users engage with media content in shared or public settings.
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August 23, 2021
April 23, 2024
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